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Forget the Data: Start with a Relationship-Based Marketing Strategy

I don’t think I’m alone when I say my life has been completely altered by data.

When I wake up in the morning, the first thing I do is check my customers’ social media accounts. Are we seeing increased activity on LinkedIn? How’s that Facebook ad campaign rolling along?

From there, I turn on Spotify, which has created the perfect playlist for me by tracking my listening preferences. Around 10:00, I’ll check my Fitbit Charge to find some motivation deep within to get moving.

Data is what establishes strategies that pay off, what allows us to investigate the past to plan for the future, what creates targeted campaigns with the precision of a Japanese Ginsu blade, and what helps our clients crawl inside their customers’ brains.

But here’s a confession: I think the industry’s obsession with metrics, segmentation, and algorithms often leads in the wrong direction, one that pushes marketers further from the ultimate goal of building lasting and meaningful relationships with customers.

Big data will only take us so far, and at some point, a human perspective needs to join the effort. “Big Data and Beyond” – Tyler Douglas

Don’t get me wrong. I understand that collecting, analyzing and correlating relevant data is key to building strategies that work.

But what I worry about is our increasing dependence on computer-based algorithms to make decisions regarding carbon-based organisms. While the deep insights culled from data can help build bridges and foster connection, marketers often miss the forest for the trees. Data becomes the bottom line, a goal unto itself–and customers wind up as mere metrics.

Ultimately, we should aim for a strategy where the right usage of the right data at the right moments lets customers know they are really being understood. The key to real relationship-building is to strike a balance between people and metrics so that they work with and enhance, one another. Here’s what I’ve learned from my own experience:

“Realize that big data and analytics will only take you so far and that ‘soft’ data that comes from activities like customer immersion, observation and direct conversations is where many organisations will find the sort of insight that will really help them stand out.” Adrian Swinscoe

Use data as part of your strategy 
Many analytics tools today do little more than adding additional complexity to the already complex challenge of understanding your customers. Businesses are collecting hoards of customer data–but most of it is just extraneous noise.

This noise will only distract you from building genuine relationships with your customers. Sure, analytics shouldn’t go neglected. But when it comes to your business strategy, it should be just one small part of engaging with your customers.

Know that numbers don’t tell the whole story. 
According to a recent Adobe study, 64% of companies have separate teams for handling online and offline data. While it may seem like an efficient business strategy, this common practice fails to take into account a holistic picture of a customer.

Ultimately, the result of our dependence on data is that we make conclusions about our customers that simply aren’t true. While it’s important to understand customer behaviors and habits to create effective campaigns and strategies, we often mistake correlation with causation when we rely on data alone.

A few companies serve as good examples of more holistic approaches to customer data analysis. Vision Critical’s Sparq, for instance, asks customers for input so that they can create broader and more human customer profiles. Getting customer input is essential for learning about customer needs and preferences and marketing your products to them accordingly.

Customer survey tools like Surveymonkey also come in handy here, because they provide customer information that’s critical when it comes to engaging with your customers on a personal level. Don’t be afraid of bad customer reviews; just as positive reviews help us by telling us what aspects of our product to maintain and even enhance, negative responses guide us in changing our products or business strategy to better suit our customers.

For small and medium-sized businesses, reaching out to customers brings more value than just their data: It also shows that you care and, in doing so, encourages ongoing customer loyalty.

Big data is here to stay, as it should be. But let’s be realistic: It’s an important resource for anyone analyzing data, not a silver bullet.- Gary Marcus, NYT

Empower your decision makers
Harnessing data should make it easier for your teams to make timely decisions. But when teams are afraid to make moves until they have analyzed “the data”, they overlook opportunities for human-to-human interaction with customers.

Consider Zappos: They’re known for their acts of kindness, like sending down-in-the-dumps customers oversized flower bouquets. The alpha-bouquet–a bouquet and card that Zappos sent immediately to the grieving daughter of a deceased customer– was an impulse so raw and authentic that it couldn’t have been scripted. If that Zappos customer service rep had to stop to read “the data” before taking action, the world would have lost out on a perfect example of deepening connections with customers.

The idea of hyper-engaging one’s customers is becoming a trend, and other companies are jumping onboard. Optimove, for example, has a real-time hyper targeting tool that helps predict customer behavior by allowing teams to pre-craft those spur-of-the-moment experiences. The end result? Your customer feels personally engaged and understood.

In order to successfully grow your business, it’s important to put in the effort to deepen your understanding of your customers. When your customers feel that you, as a business, genuinely care about their needs, they’ll feel empowered–and will keep coming back.

Use interactions to make big data human
Just as it was worth investing in your data mining toolset, it’s worth investing in sales reps who will make customers feel valued and important.

Customer relationship management (CRM) platforms are one tool that helps companies communicate more directly with customers. When sales and marketing teams have access to real-time customer data and updated product information, they can communicate with customers about their most relevant needs. Pepperi‘s mobile platform, for instance, enables salespeople to more easily address customer questions and concerns by providing them with full access to customer sales data, alongside a fully functional product e-catalog, even when they are on the road and offline.

Customer data is nothing without customer engagement. Whether you’re just starting your business or have been in the industry for years, it’s essential to interact with customers so that they feel empowered, appreciated, and committed to your brand. Otherwise, all you have is a lifeless pile of data points leading your efforts astray.

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Who’s Afraid of $5 Branding? – The Future of the Creative Industry in the Age of Automation

Those of us in the branding industry have seen several emerging trends that appear destined to integrate permanently into the way we do business. These trends are as far-reaching and diverse as businesses embracing purposeful brand activism, to the ever-growing rise of artificial intelligence in branding strategy and execution.

Friend or Foe? Artificial Intelligence and Branding

New developments in AI, such as automation and machine learning, have already creeped into the world of brand strategy and design. Through a quick analysis of user preferences and tastes, people are using AI to analyze a user’s design style and suggest appropriate fonts and logos. It’s not hard to see the appeal: automated branding takes minutes rather than days, and costs a fraction of what a human designer would charge.

Some now fear the next stage–that using machines to design and implement branding will put human designers out of work. This sort of debate isn’t new. But, despite similar protests in the past, today all sorts of automated services, from self-checkout counters at grocery stores to electronic toll booths, are commonplace.

Conversations as well as services are becoming increasingly automated; even Facebook has introduced bots that can book you a car and order you food, and Amazon’s popular Echo can automate basic tasks in your home. Given this trend, should designers be worried?

Not really. While concern in the business world may have some merit, the use of artificial intelligence for branding is decidedly different from typical examples of machine labor. While it’s true that self-checkout counters might eventually replace human cashiers, automated branding does not replace designers, nor is it likely to. Instead, automated branding opens up doors for startups and small businesses that otherwise wouldn’t have the budget for good design. And as automated branding fills this niche, designers–who could incorporate AI into their own design strategy–could benefit.

The Democratization of Branding

Well-designed branding should not be the exclusive domain of the biggest and most successful companies. Both the gig economy and the automated creative industry are now providing opportunities for small players to get a leg up in their respective fields. As is the case with hiring freelancers from sites like Task Rabbit and others, automated design providers allow humble businesses to enjoy quality work with limited budgets. Considering the kinds of expenses new businesses face, anything that helps them achieve financial independence is a good thing.

And startups aren’t the only businesses that will benefit. Automated branding companies like Tailor Brands service everyone from soccer moms making logos for team uniforms to kids who create branding for gaming clubs. They also service freelancers, dog walkers, and people pursuing their dreams after work. Sure, machine-created logos are used for traditional marketing purposes. But, they’re also amping-up your neighbor’s hobby baking business or social media profile. It’s likely these are things that users wouldn’t have hired a professional designer to do anyway.

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Small E-com, Wanna Know Why You’re Failing?

See, the veteran drivers understand the importance of knowing what’s coming next. When they race, they know what’s after each twist and turn. This allows them to apply the perfect amount of throttle, steer in the right direction, and apply brakes precisely when needed. Without knowing what’s next, a surprise turn catches many inexperienced drivers off-guard.

You may already see where this is going. Predictive analytics is the e-commerce marketer’s equal to walking the track. Do it right and you steer your business in the right direction. Ignore predictive analytics, or underestimate its importance, and risk being left in the dust. And remember, just like walking a course, there’s a right way and a wrong way to embrace predictive analytics. Here’s everything you need to know:

The Predictive Analytics Boom and Its Impact on E-commerce Marketers Today

Steadily but surely, predictive analytics has been gaining in popularity. It’s expected to explode this year as it becomes more accessible and goes from being a competitive advantage to a necessity. To fully understand how it impacts e-commerce marketers today, first we’ve got to look back to the past.

Traditionally, predictive analytics has been reserved for top brands such as eBay and Netflix. eBay is focused on using predictive analytics to make its shopping experience better for both buyers and sellers. Indeed, eBay considered predictive analytics so important that it acquired SalesPredict to boost its AI, machine learning and data science efforts.

When a company like eBay spends millions on an acquisition for the sake of predictive analytics, e-commerce marketers must take note.

There are a couple of reasons that eBay made this move:

  • Better understanding of what their customers wanted.
  • Access to advanced insights for improving conversion rates and accelerating sales cycles.
  • More targeted offers with relevant information for buyers.
  • The ability to build-out predictive models that can define the probability of selling a given product at a given price over time.

In other words, predictive analytics answers some of the biggest challenges facing e-commerce marketers and business owners.

How to Use Predictive Analytics Like eBay Does

To achieve similar benefits to eBay, you only need to take the following four steps:

  • Track e-commerce metrics and create a one-day forecast. Then identify any deviation between the forecast and the actual metrics.
  • Determine the cause of deviations from your one-day predictions. Assuming the deviation can be minimized, take steps to do so; otherwise, use it to establish a confidence level in your predictions.
  • Create progressively longer-term predictions, ranging from one day to 18 months.
  • Use predictions to answer “what if” questions such as, “What if we increase advertising spend?” or “what if we decrease stock for this item?” and more.

Obviously, it’s easier said than done, but with the proper tools and strategy, you can be predicting the future in no time.

Overcoming Common Challenges

Predictive analytics isn’t without its challenges. For one, it can be difficult to trust the data, especially when your “gut” and past experiences may indicate otherwise. But even more challenging is doing predictive analytics right.

Ensuring Data Quality and Managing Data From Multiple Sources

Remember how the first step of using predictive analytics involved creating a one-day prediction, then testing that prediction’s accuracy? That is the key to ensuring quality data. Start small with predictive analytics and only move up to more complex/long-term predictions when you’re ready for it.

At first, your data may make a significant impact (especially if you’re still in the one-day prediction phase), but taking the time to validate predictions will ensure that your data won’t lead you astray. Validating your data is a neverending process, as well. You’ll need to put a system in place to routinely check metrics and ensure they are accurate.

One of the other common challenges is managing multiple data sources. Difficulties in multiple data sources can be minimized by utilizing a BI tool that integrates with hundreds of sources. This will ensure that all your data is kept in one place and can be easily accessed and analyzed.

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Revenue Hack/Growth Hack: The Secrets to Selling Online

In a competitive business world of big ideas and small attention spans, it is a challenge in and of itself to compel onlookers to turn into customers. What a lot of industries fail to recognize is that by giving these onlookers subtle, but very real, incentives to buy your product or service, you are substantially increasing your odds of converting sales. Below are 5 ideas as to how you can, and will, do just that:

Limited Time Offers

By pushing a limited time offer onto your potential customers, you apply a sense of pressure (but nothing invasive) to viewers who are on-the-fence about your product or service. Simply put, people feel compelled to meet deadlines, especially when there is the notion of scarcity. In this case, time is of the essence. For example, the world renowned Air Jordan sneakers have seen time and again the lengths people will go to get their hands on a limited product.

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8 Myths Uncovered about the Role of Social Media in Online Reviews

Thanks to social media and the growing prevalence of rating sites such as Yelp, TripAdvisor, FourSquare, and the like, consumers are gaining greater access to useful reviews that extend beyond the almighty word-of-mouth recommendation or condemnation.

Here, we’re uncovering 8 myths commonly ascribed to the role of social media in online reviews:

Myth #1: My business needs to be present on every social network

This myth is perhaps the saddest and most misinformed of the bunch—if you’re trying to rake up likes, follows, and comments across every social network and ranking platform possible, you might as well be chasing your tail, as it’ll be a never-ending game of catch-up that won’t be worth the time and effort invested. Instead of spreading yourself thin, focus on the platforms where your greatest audience segments already spend their time and interact with your business. Though your customers may be present on all such platforms, focus your time and attention on those with the greatest engagement with your brand, and respond accordingly.

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